جستجوی استاد راهنمای دانشگاهی

Dean Hougenمشاهده پروفایل

استاد

• Artificial Intelligence
• Robotics
• Machine Learning
• +۴ مورد دیگر

Dean F. Hougen is the Lloyd & Joyce Austin Presidential Professor and Director of the School of Computer Science at the University of Oklahoma. He holds faculty appointments in the School of Electrical and Computer Engineering and the Data Science and Analytics Institute . His research focuses on Artificial Intelligence (AI) , Robotics , Machine Learning , and Computer Science Education . Education: Ph.D. in Computer Science, University of Minnesota (1998) B.S. in Computer Science, Iowa State University (1988) Research Interests: Dr. Hougen’s work spans AI/ML systems, robotics, interpretable machine learning, evolutionary computation, and ethics in technology. He emphasizes practical applications in healthcare, aerospace, and education. Grants and Projects: He has secured $24M+ in funding, including leadership roles in projects like Operationalizing Additive Manufacturing (Air Force Research Lab) and Predictive Intelligence for Pandemic Prevention (NSF). Recent collaborations include work with Boeing, NASA, and international institutions. Awards: Highlights include the Austin Presidential Professorship (2022), multiple best paper awards, and teaching recognitions such as Professor of the Year (2015-2016). Labs: Leads the Artificial Intelligence Research (AIR) Superlab and Robotic Intelligence and Machine Learning Laboratory (RIML Lab) .

• Robotics
• Artificial Intelligence
• Evolutionary Computing
• +۱۲ مورد دیگر

Kyrre Harald Glette is a Professor in the Department for Informatics at the University of Oslo , affiliated with the Robotics and Intelligent Systems Research Group and the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion . His research focuses on the co-design of robot morphology and control using evolutionary and bio-inspired artificial intelligence methods. Research Interests: Robotics and Intelligent Systems Evolutionary Robotics and Co-Design of Morphology and Control Artificial Intelligence and Machine Learning Evolvable Hardware and Embodied Computation Computational Creativity and Music-AI Interaction Human-Robot Interaction and Swarm Robotics His recent publications (2023–2025) reflect a strong interdisciplinary trend, combining robotics, evolutionary computation, and music technology. Key themes include evolutionary design of modular robots , real-time adaptation in bio-inspired systems , interactive sonification , and AI-driven music generation . His work often involves the DyRET robotic platform, emphasizing real-world evolution and embodied learning. Scientific Contributions: Extensive publications in top venues like Frontiers in Robotics and AI , IEEE ICRA , GECCO , and Nature Machine Intelligence . Development of open-source robotic platforms and frameworks for evolutionary robotics. Interdisciplinary work bridging AI, neuroscience, and music. Advising and Projects: He supervises MSc students in evolutionary robotics, robot locomotion, and musical robot swarms. He is involved in several research projects including Predictive and Intuitive Robot Companion (PIRC) , Modeling and Robots , Multimodal Elderly Care Systems (MECS) , Musical Human-Machine Interaction , and Neurophysiological Mechanisms of Human Auditory Predictions (AudioPred) . Labs and Research Groups: He is a key member of the Robotics and Intelligent Systems (ROBIN) group, the RITMO Centre of Excellence , and the Creative Computing Hub Oslo (C2HO) . These groups support interdisciplinary research in AI, robotics, music, and human interaction.

• Intelligent Transport Systems (ITS)
• Road Safety
• Human Factors Engineering
• +۴ مورد دیگر

Professor Andry Rakotonirainy is a renowned expert in road safety and Intelligent Transport Systems (ITS) at QUT's Faculty of Health, School of Psychology & Counselling. He holds a PhD in Computer Science from Sorbonne University and INRIA, France. His research focuses on human factors in ITS, leveraging computer science, engineering, and psychology to improve road safety. He leads the ITS human factors program at CARRS-Q and the Centre for Future Mobility, with over $76M in research grants. Key roles include ARC College of Experts membership and EU project advisory roles. Research Interests: Connected and Automated Vehicles (CAVs) Eco-safe driving systems Human-Machine Interaction Driver Behavior Analysis Transportation Policy Projects: EU-funded LEVITATE (€6.4M) studying societal impacts of CAVs Queensland CAVI-iMOVE CRC initiative ARC grants on AI explainability and AV safety Achievements: Over 300 publications, h-index 45, and 14 ARC grants. Established ICCAM with Université Gustave Eiffel. Advising & Grants: Supervised 6 doctoral and 2 master's students. Active in government/industry committees and grant reviews. Labs/Teams: CARRS-Q, Centre for Future Mobility, and ICCAM collaboration.

Eugene Santos Jr.مشاهده پروفایل

استاد

• Artificial Intelligence
• Decision-Making Systems
• Adversarial Modeling
• +۶ مورد دیگر

Eugene Santos Jr. is the Sydney E. Junkins 1887 Professor of Engineering and Director of the Master of Engineering Program at Dartmouth College's Thayer School of Engineering. He holds adjunct roles in Computer Science and serves on the Department of the Air Force Scientific Advisory Board. His research bridges artificial intelligence, decision science, and social systems, focusing on computational intent, adversarial modeling, and explainable AI applications in healthcare, cybersecurity, and societal resilience. Education: BS/MS in Math/CS (Youngstown State), ScM/PhD in Computer Science (Brown University). Awards include AAAS and IEEE Fellowships. Key projects include AI ethics frameworks, insider threat detection, and federated biomedical knowledge graphs. Research interests span Bayesian knowledge systems, human-machine teaming, and nonlinear decision-making. Over 150 peer-reviewed publications include advancements in reward function analysis, ontology fusion, and trust in AI systems. Advised 10+ PhD students and leads the DI²AG research group. Active in policy roles, including Vermont's AI Taskforce and editorial leadership for IEEE Transactions on Cybernetics.

• Robotics
• Human-Robot Interaction
• Industrial Automation
• +۳ مورد دیگر

Alexandre Angleraud is a Postdoctoral Research Fellow at Tampere University within the Automation Technology and Mechanical Engineering department under the Faculty of Engineering and Natural Sciences. His research focuses on advancing human-robot collaboration, robotic manipulation, and sensor-based systems in industrial and manufacturing environments. Key areas include knowledge-based planning, tactile feedback learning, and cognitive semantics for dynamic task coordination. His work integrates robotics with machine learning techniques, emphasizing agile production systems, soft robotic grippers, and natural language interfaces for hierarchical task instruction. Notable contributions include innovations in multi-label annotation for visual models and exploration-exploitation mechanisms inspired by neural processes. Recent research trends highlight advancements in co-speech gesture interpretation for human-robot interaction, imitation learning frameworks leveraging sequential data, and comparative studies on sim-to-real learning controllers. His studies often bridge theoretical cognitive models with practical industrial automation challenges. No scientific awards or funded grants are explicitly listed in the provided materials. Advising activities and lab affiliations remain unspecified in the current data.

• Computational Linguistics
• Natural Language Processing
• Vision-Language Models
• +۵ مورد دیگر

Joyce Chai is a prominent academic researcher in computational linguistics and AI with extensive contributions to grounded language learning, embodied agents, and human-machine collaboration. Her work spans vision-language models, theory of mind implementation, and task guidance systems. Key research themes: Language grounding in physical/social contexts Embodied AI and situated reasoning Interactive learning frameworks Zero-shot and continual concept acquisition Recent publications demonstrate her leadership in: Developing TRAVER for coding tutoring agents Creating W2W grounded language model Advancing theory of mind evaluation in LLMs Establishing HAR reasoning strategies for coherent physical reasoning She has mentored numerous students including Ziqiao Ma, Shane Storks, and Yuwei Bao. Her work appears in top venues like ACL, EMNLP, and NAACL with focus on practical applications like cake-making guidance systems (WTaG) and autonomous driving dialogue (DOROTHIE). Technical contributions include: MetaReVision retrieval-enhanced meta-learning EpiCA network for compositional concept recognition Neuro-symbolic DANLI agent architecture Pragmatic Rational Speaker framework

• Autonomous Systems
• User Modeling
• Personalization
• +۳ مورد دیگر

Marek Piasecki is a researcher at the Department of Computer Engineering, Faculty of Information and Communication Technology, Wrocław University of Science and Technology. His work focuses on software development for autonomous systems, user modeling, personalization, and mobile computing. His research in autonomous systems includes classical and reactive navigation, localization, and path planning for mobile robots, particularly in the RoboCup competition. He has extensively explored automatic recommendation systems and software development for mobile devices, blending both Android and iOS platforms. The articles he has published demonstrate strong engagement with robotics, autonomous systems, and mobile computing. Key areas include evolutionary algorithms, differential mapping, IoT applications, and educational robotics (LEGO Mindstorms). These works span theoretical development, software implementation, and pedagogical approaches. In teaching, he specializes in C++, C, and Java programming languages, object-oriented programming, and software engineering principles. He also leads seminars on constructing mobile robots and supervises diploma projects involving mobile robotics and software development.

• Robotics
• Cybersecurity
• Machine Learning
• +۴ مورد دیگر

ÁNGEL MANUEL GUERRERO HIGUERAS is an Associate Professor at the Department of Mechanical, Computer and Aerospace Engineering, School of Industrial, Informatics and Aerospace Engineering, University of León. His research focuses on Robotics, Cybersecurity, and Machine Learning , with emphasis on autonomous systems, human-robot interaction, and network threat detection. PhD in Computer Science (2017) from University of León Research areas include Edge AI, Vision-Language Models, Post-Quantum Cryptography Active in Explainable AI for robotics and blockchain-based accountability Recent publications (2023-2025) span topics like LLM integration in robotics, autonomous system security, and flow-based anomaly detection. His work bridges theoretical research with practical applications in robotic platforms and network defense.

José Fernando Lopes Barbosaمشاهده پروفایل

استاد مدعو

• Cyber-Physical Systems
• Multi-Agent Systems
• Manufacturing Automation
• +۳ مورد دیگر

José Barbosa is a Senior Researcher at the Research Centre in Digitalization and Intelligent Robotics (CeDRI) and an Invited Professor at the Department of Electrical Engineering, Polytechnic Institute of Bragança, Portugal. He holds a PhD in Automation and Computer Science from the University of Valenciennes (France) and has extensive experience in European-funded projects like ARUM, GRACE, DA.RE, GO0DMAN, and PERFoRM. His expertise spans Cyber-Physical Systems, Multi-Agent Systems, and manufacturing automation, with over 40 international publications. Research focuses on self-organizing manufacturing architectures, digital twins, and bio-inspired mechanisms. He teaches courses including Microcontroller/Microprocessor Systems, Automation, and Electric Propulsion. Projects emphasize Industry 4.0, zero-defect manufacturing, and intelligent products. His work intersects IoT, data analytics, and human-machine integration in industrial systems.

Jeff Cluneمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Neuroevolution
• +۵ مورد دیگر

Jeff Clune is a Professor in the Department of Computer Science at the University of British Columbia (UBC), Canada, and a Canada CIFAR AI Chair at the Vector Institute. He also serves as a Senior Research Advisor at DeepMind. His work focuses on advancing artificial intelligence through evolutionary computation, neuroevolution, and open-ended systems. Clune's research explores topics such as continual learning, generative models (e.g., Genie), and automated scientific discovery. He is known for developing algorithms like Go-Explore and pioneering methods in neuroevolution to create robust and adaptable AI systems. His academic affiliations include the UBC Faculty of Science and collaborations with industry leaders like DeepMind. Clune teaches courses on machine learning and data mining, emphasizing practical applications and theoretical foundations. His awards include the SIGEVO Impact Award and recognition for outstanding publications in AI research. Notable projects include the development of the Go-Explore algorithm and contributions to AI safety and ethical frameworks. Clune's work bridges biological inspiration with machine learning, aiming to create systems that evolve and learn like natural organisms. Research interests span AI safety, generative AI, robotics, and scalable learning algorithms. He has published extensively on topics like neural network dynamics, open-endedness, and automated experimentation. Current projects include enhancing AI's ability to self-improve and exploring ethical implications of advanced AI systems.

Johannes Fottnerمشاهده پروفایل

استاد

• Technical Logistics
• Material Flow Optimization
• RFID Technology
• +۵ مورد دیگر

Prof. Dr.-Ing. Johannes Fottner is a full professor of Technical Logistics at the Technical University of Munich (TUM), affiliated with both the TUM School of Engineering and Design and the TUM School of Management. He holds a doctorate in mechanical engineering from TUM (2002) and has extensive industry experience, including leadership roles at Swisslog Group (2002–2008) and MIAS Group (2008–2016). His academic work focuses on material flow optimization, RFID technology integration, and practical applications for SMEs. He leads the Logistics Innovation Center (liz) and RFID Application Center Munich (RFID-AZM) at TUM. Research interests include: Control and optimization of material flow processes using RFID Logistics planning with digital tools Human factors in logistics automation Sustainable logistics systems and circular economy AI-driven decision-making in supply chains His articles emphasize cutting-edge topics like AI integration in healthcare logistics, digital twins for long-lasting systems, and AMR communication protocols. Awards include the 2003 Rudolf Schmidt-Burkhardt Memorial Prize. He actively bridges academic research with industrial practice, particularly in SME contexts. Current projects explore self-optimizing supply chains and predictive analytics for logistics KPIs. Key contributions also include: Development of modular warehouse allocation algorithms Standardization of screw conveyor designs across global industries Advocacy for system-level thinking in construction automation Led TUM's 2024 Fachtagung Schüttgutfördertechnik conference and collaborates internationally on robotics in construction and recycling. Active in professional societies like VDI, serving as deputy chairman of its Production and Logistics Society.

Orestis Papakyriakopoulosمشاهده پروفایل

استاد

• Societal Computing
• Artificial Intelligence Ethics
• Data Science
• +۳ مورد دیگر

Prof. Dr. Orestis Papakyriakopoulos is a faculty member at the Technical University of Munich (TUM), holding the position of Professor of Societal Computing within the School of Social Sciences and Technology. His research focuses on equitable socio-algorithmic ecosystems, AI ethics, and the societal implications of data-driven technologies. He holds a Dipl. Ing. in Civil Engineering from the National Technical University of Athens, an MA in Philosophy of Science and Technology from TUM, and a PhD in Computer Science from TUM. Before joining TUM in 2024, he was a visiting scholar at MIT Media Lab, conducted postdoctoral research at Princeton University, and worked as an AI research scientist at Sony. His research interests include algorithmic bias mitigation, political communication on social media, and the ethical challenges of AI systems. He has extensively studied platforms like TikTok, Reddit, and YouTube, analyzing how algorithms shape political discourse and influence public opinion. Key themes in his recent work include cross-national attitudes toward facial analysis AI, the sociotechnical alignment of AI with human values, and the design of responsible data curation frameworks. His publications often bridge technical innovations with critical societal analysis. Prof. Papakyriakopoulos has contributed to policy debates on AI ethics and digital governance, particularly in Europe. He advises on transparency in political advertising and has collaborated on initiatives to combat misinformation, including studies on vaccine perceptions during the early phases of the U.S. rollout.

Eduard Paul Enoiuمشاهده پروفایل

دانشیار

• Software Engineering
• Empirical Research
• Automated Test Generation
• +۷ مورد دیگر

Eduard Paul Enoiu is an Associate Professor at Mälardalen University's Department of Networked and Embedded Systems, affiliated with the Software Testing Laboratory and Formal Modelling and Analysis groups. He holds a PhD from Mälardalen University (2016) and an Engineer's degree from Polytechnic University of Bucharest (2009). His research focuses on software engineering, empirical studies in testing, automated test generation, and model-based verification. He teaches automated testing at master’s/PhD levels and industrial practitioners. Current research includes cognitive aspects of testing, ethical considerations, and applying AI in DevOps security. He advises theses in software testing and embedded systems development. **Education:** PhD in Software Engineering (2016), Mälardalen University Engineer's degree (2009), Polytechnic University of Bucharest **Research Interests:** Automated test generation and optimization Formal verification of embedded systems Cognitive psychology in software testing Requirements engineering and reuse Security validation in DevOps Ethical and human factors in testing **Labs/Teams:** Software Testing Laboratory Formal Modelling and Analysis of Embedded Systems group

Dhaminda Abeywickramaمشاهده پروفایل

پژوهشگر ارشد

• Autonomous Systems
• Assurance Engineering
• Formal Verification
• +۷ مورد دیگر

Roles and Affiliations: Dhaminda Abeywickrama is a Research Fellow in Autonomous Systems at the University of Manchester's Department of Computer Science. He leads assurance research for robotics and autonomous systems (RAS), focusing on safety, ethics, and security. His work is part of CRADLE, a center developing technologies for high-stakes industries like space and energy. Previously, he held roles at the University of Bristol (UKRI TAS Node in Functionality) and University of Warwick (agent-based norms research). He completed ERCIM and Marie Curie fellowships at VTT (Finland) and Fraunhofer FOKUS (Germany), with a focus on autonomic systems. Education: PhD in Software Engineering, Monash University (2010) First Class Honours in Computing, Monash University (2004) Research Interests: His expertise spans assurance engineering, autonomous systems, formal verification, multi-agent systems, and responsible AI. He develops frameworks for trustworthy robotics through model-driven design and dynamic assurance techniques. Key themes include emergent behavior analysis, sociotechnical risk modeling, and ethical decision-making in human-agent collectives. Publications: His work emphasizes cross-disciplinary approaches to assurance in robotics, with recent focus on swarm verification and trustworthiness specifications. Over 35 publications include peer-reviewed articles and conference papers, with 32 as first author. Key topics include robotic swarm validation, ethical AI, and self-adaptive system architectures. Awards and Grants: EU Marie Curie Fellowship (2013–2014) ERCIM Fellowship (2013–2017) Best Paper Award at WETICE’14 IBM Award at ICSOC’08 PhD Symposium Labs and Collaborations: CRADLE (University of Manchester), UKRI TAS Node (Bristol), and collaborations across academia and industry (e.g., Jaguar Land Rover, Volkswagen AG). Research integrates formal methods with real-world applications in robotics, safety-critical systems, and autonomous vehicle coordination.

Elizabeth Blackمشاهده پروفایل

استاد

• Artificial Intelligence
• Multi-Agent Systems
• Argumentation Theory
• +۳ مورد دیگر

Elizabeth Black is a Professor of Artificial Intelligence at King's College London's Department of Informatics, part of the Faculty of Natural, Mathematical & Engineering Sciences. She leads the UKRI Centre for Doctoral Training in Safe and Trusted Artificial Intelligence, collaborating with Imperial College London to develop AI systems with ethical and safety guarantees. She serves on the steering committee of the COMMA conference series and the editorial board of Autonomous Agents and Multi-Agent Systems . Her research focuses on argumentation theory, multi-agent systems, AI ethics, and healthcare informatics. Education: PhD in Computer Science (2007, UCL), Postdoctoral research at Oxford University and a Marie-Curie Fellowship at Utrecht University. Research Interests: Elizabeth explores AI's societal impact through argumentation frameworks, ethical AI design, and applications in healthcare. Her work bridges formal logic with practical systems, addressing transparency and fairness in AI decision-making. Articles: Recent work emphasizes fair machine learning, bias mitigation, and neuroevolution techniques. Her publications span dialogue systems, AI ethics, and multi-agent coordination, reflecting interdisciplinary engagement with computational models of argument and social AI. Awards: Fellow of the Higher Education Academy (2021). Grants & Projects: Leads the PHAWM project (EPSRC-funded participatory harm auditing workbenches) and previously worked on commodity market transparency (TSB) and automated argument planning (EPSRC). Supervises PhD students in AI ethics and argumentation systems. Labs/Teams: Member of the Reasoning and Planning research group, contributing to the UK's Trusted Autonomous Systems Hub. Active in organizing workshops like TAFA and ArgMAS on formal argumentation.